remember

Review the current conversation and capture valuable knowledge — best practices, coding conventions, architecture decisions, workflows, and user feedback —…

npx skills add https://github.com/langchain-ai/deepagents --skill remember

Review our conversation and capture valuable knowledge. Focus especially on best practices we discussed or discovered—these are the most important things to preserve.

Step 1: Identify Best Practices and Key Learnings

Scan the conversation for:

Best Practices (highest priority)

  • Patterns that worked well - approaches, techniques, or solutions we found effective
  • Anti-patterns to avoid - mistakes, gotchas, or approaches that caused problems
  • Quality standards - criteria we established for good code, documentation, or processes
  • Decision rationale - why we chose one approach over another

Other Valuable Knowledge

  • Coding conventions and style preferences
  • Project architecture decisions
  • Workflows and processes we developed
  • Tools, libraries, or techniques worth remembering
  • Feedback I gave about your behavior or outputs

Step 2: Decide Where to Store Each Learning

For each best practice or learning, choose the right destination:

-> Memory (AGENTS.md) for preferences and guidelines

Use memory when the knowledge is:

  • A preference or guideline (not a multi-step process)
  • Something to always keep in mind
  • A simple rule or pattern

Global (~/.deepagents/agent/AGENTS.md): Universal preferences across all projects Project (.deepagents/AGENTS.md): Project-specific conventions and decisions

-> Skill for reusable workflows and methodologies

Create a skill when we developed:

  • A multi-step process worth reusing
  • A methodology for a specific type of task
  • A workflow with best practices baked in
  • A procedure that should be followed consistently

Skills are more powerful than memory entries because they can encode how to do something well, not just what to remember.

Step 3: Create Skills for Significant Best Practices

If we established best practices around a workflow or process, capture them in a skill.

Example: If we discussed best practices for code review, create a code-review skill that encodes those practices into a reusable workflow.

Skill Location

~/.deepagents/agent/skills/<skill-name>/SKILL.md

Skill Structure

skill-name/
├── SKILL.md          (required - main instructions with best practices)
├── scripts/          (optional - executable code)
├── references/       (optional - detailed documentation)
└── assets/           (optional - templates, examples)

SKILL.md Format

---
name: skill-name
description: "What this skill does AND when to use it. Include triggers like 'when the user asks to X' or 'when working with Y'. This description determines when the skill activates."
---

# Skill Name

## Overview
Brief explanation of what this skill accomplishes.

## Best Practices
Capture the key best practices upfront:
- Best practice 1: explanation
- Best practice 2: explanation

## Process
Step-by-step instructions (imperative form):
1. First, do X
2. Then, do Y
3. Finally, do Z

## Common Pitfalls
- Pitfall to avoid and why
- Another anti-pattern we discovered

Key Principles

  1. Encode best practices prominently - Put them near the top so they guide the entire workflow
  2. Concise is key - Only include non-obvious knowledge. Every paragraph should justify its token cost.
  3. Clear triggers - The description determines when the skill activates. Be specific.
  4. Imperative form - Write as commands: "Create a file" not "You should create a file"
  5. Include anti-patterns - What NOT to do is often as valuable as what to do

Step 4: Update Memory for Simpler Learnings

For preferences, guidelines, and simple rules that don't warrant a full skill:

## Best Practices
- When doing X, always Y because Z
- Avoid A because it leads to B

Use edit_file to update existing files or write_file to create new ones.

Step 5: Summarize Changes

List what you captured and where you stored it:

  • Skills created (with key best practices encoded)
  • Memory entries added (with location)

Lebih banyak skill dari langchain-ai

langgraph-docs
langchain-ai
Mengakses dokumentasi LangGraph untuk membangun agen stateful dan alur kerja multi-agen. Mengambil dokumentasi resmi LangGraph Python yang mencakup mesin state, desain agen berbasis grafik, dan pola human-in-the-loop. Memprioritaskan dokumentasi yang relevan berdasarkan jenis kueri: panduan implementasi untuk pertanyaan cara, halaman konsep untuk teori, tutorial untuk contoh ujung ke ujung, dan referensi API untuk detail teknis. Secara otomatis memilih 2–4 URL dokumentasi yang paling relevan dan mengambil kontennya untuk menjawab...
official
langgraph-human-in-the-loop
langchain-ai
Jeda eksekusi graf untuk peninjauan, persetujuan, atau validasi manusia, lalu lanjutkan dengan masukan mereka. Membutuhkan tiga komponen: checkpointer (InMemorySaver atau PostgresSaver), ID thread dalam konfigurasi, dan payload interupsi yang dapat diserialisasi JSON. interrupt(value) menjeda dan menampilkan data; Command(resume=value) melanjutkan dan mengembalikan nilai tersebut ke node yang dijeda. Semua kode sebelum interrupt() akan dieksekusi ulang saat melanjutkan, sehingga efek samping harus idempoten (gunakan upsert, bukan insert). Mendukung alur kerja persetujuan,...
official
web-research
langchain-ai
Gunakan keterampilan ini untuk permintaan yang terkait dengan riset web; ini menyediakan pendekatan terstruktur untuk melakukan riset web yang komprehensif.
official
langchain-oss-primer
langchain-ai
SELALU MULAI DI SINI untuk proyek pembuatan agen LangChain, Deep Agents, atau LangGraph apa pun. Titik awal yang diperlukan sebelum memilih keterampilan lain atau menulis apa pun…
official
skill-creator
langchain-ai
Panduan untuk membuat skill yang efektif guna memperluas kemampuan agen dengan pengetahuan khusus, alur kerja, atau integrasi alat. Gunakan skill ini ketika pengguna…
official
social-media
langchain-ai
Menyusun draf posting media sosial khusus platform dengan konten berbasis riset dan gambar pendamping yang dihasilkan. Mendukung posting LinkedIn (1.300 karakter dengan nada profesional) dan utas Twitter/X (280 karakter per tweet dengan format 1/🧵). Memerlukan delegasi riset ke subagen sebelum menulis, kemudian membaca temuan untuk memastikan akurasi dan relevansi. Menghasilkan gambar sosial yang menarik secara otomatis menggunakan alat generate_social_image dengan komposisi tebal dan kontras tinggi yang dioptimalkan untuk ukuran kecil...
official
deep-agents-memory
langchain-ai
Backend memori dan file yang dapat dipasang untuk Deep Agents dengan opsi perutean sementara, persisten, dan hibrida. Empat jenis backend: StateBackend (berlaku dalam thread, sementara), StoreBackend (persisten lintas sesi), FilesystemBackend (akses disk nyata untuk pengembangan lokal), dan CompositeBackend (merutekan jalur berbeda ke backend berbeda). FilesystemMiddleware menyediakan enam alat operasi file: ls, read_file, write_file, edit_file, glob, grep. CompositeBackend menggunakan pencocokan prefiks terpanjang untuk merutekan...
official
deep-agents-orchestration
langchain-ai
We need to translate the given English text into Indonesian. The text describes an agent skill for orchestrating subagents, planning tasks, requiring human approval, delegating work, etc. We must preserve product names, protocol names, URLs, numbers, technical terms. The name "deep-agents-orchestration" is not in the text, so we don't include it. We translate only the text inside <text>. No extra commentary, labels, etc. Let's translate step by step: "Orchestrate subagents, plan multi-step tasks, and require human approval for sensitive operations." -> "Orkestrasi subagen, rencanakan tugas multi-langkah, dan minta persetujuan manusia untuk operasi sensitif." "Delegate work to specialized subagents via the task tool; custom subagents support isolated tool sets and system prompts, while the default "general-purpose" subagent inherits main agent configuration" -> "Delegasikan pekerjaan ke subagen khusus melalui alat tugas; subagen kustom mendukung set alat dan prompt sistem yang terisolasi, s
official